{"title":"Artificial Intelligence for a Better Employee Engagement","authors":"Ria Emilia Sari, Siu Min, Hiskia Purwoko, Asnan Furinto, D. Tamara","doi":"10.21632/IRJBS.13.2.173-188","DOIUrl":null,"url":null,"abstract":"Employee engagement is the positive attitude of each employee towards the business and the value of the organization. This research aims to see whether the use of AI-based technology, tools, and software can help management detect intangible things such as employee engagement level and provide clues as to what factors influence it and how management can improve it. This research is a qualitative approach. We interviewed the management and selected employees to determine employee engagement at SML before and after implementing the AI-based application. The interview results compared with the results obtained from the application for six months (Feb - July 2020). The study was conducted on all SML employees, amounting to 39 people. This research has shown that the use of AI based software can significantly help management, not only to find out the status of each employee’s level of involvement but also to anticipate their attitudes and behaviors through predictive indicators. Thus, the company can proactively retain key employees. This research provides new and practical insights and opportunities for company owners and leaders to utilize technology to detect something that is naturally quite difficult because it requires specific knowledge and experience Keywords: engagement, employee engagement, work engagement, technology, technology enabler, artificial intelligence, software, application. * Magister Manajemen BINUS Business School, Universitas Bina Nusantara, Jl. Hang Lekir I No. 6, Senayan, Kebayoran Baru, Jakarta Selatan, DKI Jakarta. https://doi.org/10.21632/irjbs.13.2.173-188","PeriodicalId":31166,"journal":{"name":"International Research Journal of Business Studies","volume":"13 1","pages":"173-188"},"PeriodicalIF":0.0000,"publicationDate":"2020-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Research Journal of Business Studies","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.21632/IRJBS.13.2.173-188","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 6
Abstract
Employee engagement is the positive attitude of each employee towards the business and the value of the organization. This research aims to see whether the use of AI-based technology, tools, and software can help management detect intangible things such as employee engagement level and provide clues as to what factors influence it and how management can improve it. This research is a qualitative approach. We interviewed the management and selected employees to determine employee engagement at SML before and after implementing the AI-based application. The interview results compared with the results obtained from the application for six months (Feb - July 2020). The study was conducted on all SML employees, amounting to 39 people. This research has shown that the use of AI based software can significantly help management, not only to find out the status of each employee’s level of involvement but also to anticipate their attitudes and behaviors through predictive indicators. Thus, the company can proactively retain key employees. This research provides new and practical insights and opportunities for company owners and leaders to utilize technology to detect something that is naturally quite difficult because it requires specific knowledge and experience Keywords: engagement, employee engagement, work engagement, technology, technology enabler, artificial intelligence, software, application. * Magister Manajemen BINUS Business School, Universitas Bina Nusantara, Jl. Hang Lekir I No. 6, Senayan, Kebayoran Baru, Jakarta Selatan, DKI Jakarta. https://doi.org/10.21632/irjbs.13.2.173-188
员工敬业度是每个员工对业务和组织价值的积极态度。本研究旨在了解使用基于人工智能的技术、工具和软件是否可以帮助管理层检测员工敬业度等无形因素,并提供影响因素以及管理层如何改进的线索。本研究采用定性方法。我们采访了管理层并选择了员工,以确定SML在实施基于人工智能的应用程序之前和之后的员工敬业度。将面试结果与六个月(2020年2月- 7月)的申请结果进行比较。这项研究是对所有SML员工进行的,共计39人。本研究表明,使用基于AI的软件可以显著帮助管理层,不仅可以了解每个员工的参与程度,还可以通过预测指标预测他们的态度和行为。因此,公司可以主动留住关键员工。这项研究为公司所有者和领导者提供了新的和实用的见解和机会,以利用技术来检测一些自然相当困难的事情,因为它需要特定的知识和经验。关键词:敬业度,员工敬业度,工作敬业度,技术,技术推动者,人工智能,软件,应用程序。*马来西亚比那努桑塔拉大学工商管理学院管理部长Hang Lekir I No. 6, Senayan, Kebayoran Baru, Jakarta Selatan, DKI Jakarta。https://doi.org/10.21632/irjbs.13.2.173-188